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SnapHiC: a computational pipeline to identify chromatin loops from single-cell Hi-C data
Miao Yu1,2, Armen Abnousi3, Yanxiao Zhang2
1State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China.
Nature Methods
|August 27, 2021
Summary
A new computational tool, SnapHiC, accurately identifies high-resolution chromatin loops from single-cell Hi-C data. This method aids in understanding cell-specific gene regulation and potential disease mechanisms.
Area of Science:
- Genomics
- Epigenetics
- Computational Biology
Background:
- Single-cell Hi-C (scHi-C) is crucial for mapping 3D genome organization in various tissues.
- Existing computational tools struggle to define high-resolution chromatin loops from scHi-C data.
Purpose of the Study:
- Introduce SnapHiC, a novel computational method for high-resolution chromatin loop identification from scHi-C data.
- Validate SnapHiC's accuracy and performance against existing tools.
Main Methods:
- Developed and applied the Single-Nucleus Analysis Pipeline for Hi-C (SnapHiC).
- Benchmarked SnapHiC using scHi-C data from 742 mouse embryonic stem cells.
- Analyzed single-nucleus methyl-3C-seq data from 2,869 human prefrontal cortical cells.
Main Results:
- SnapHiC accurately identifies chromatin loops at high resolution from scHi-C data.
- Demonstrated SnapHiC's utility in uncovering cell type-specific chromatin loops in human brain tissue.
- Identified putative target genes for noncoding variants linked to neuropsychiatric disorders.
Conclusions:
- SnapHiC provides a robust solution for analyzing cell type-specific chromatin architecture.
- The method facilitates the study of gene regulatory programs in complex biological systems.
- SnapHiC has implications for understanding the genetic basis of neuropsychiatric disorders.
